Download this [zipped folder] (https://github.com/rswaty/landfireFSC/blob/main/toDownload.zip) by clicking the hyperlinked text, then the “Download” button that will be on the right side of the screen. This folder contains:
Open ArcGIS Pro and create a new project using a blank map template. Move the downloaded Ataya shapefile tutorial data into your project folder.
Note that Pro creates a default geodatabase with the same name as your project. We recommend saving the Ataya shapefile to your geodatabase and hereafter, save intermediate layers to your geodatabase.
Consider your study area: Is it appropriate to end your analysis at the shapefile boundary? If you would like information to extend beyond the study boundary, consider creating a buffer. For our tutorial, we will limit our analysis to within the provided Ataya forest tract boundary.
There are multiple ways to get LANDFIRE products.
For some LANDFIRE data products, like the BpS model, the model (spatial data) and descriptions are downloaded separately: * For BpS models and descriptions go to: http://landfirereview.org/search.php. Start by clicking on the “View map of LANDFIRE Map Zones”. This will help you narrow down your search. We recommend downloading descriptions for BpS models relevant to your study area.
Note that for this tutorial, we downloaded rasters by using the rectangle drawing tool and drew a rectangle that was larger than our Study Area. This ensures no raster cell data is lost in our calculations. This tutorial allows us to “cut” out that extra area in the end. If you are downloading your own data, always make sure to draw a downloading box that is larger than your Study Area to prevent GIS errors.
Once downloaded, move the LANDFIRE data product downloads into your Pro project folder. You should have a BpS, EVT, and SCLASS folder. Each folder contains metadata, a corresponding database table, and a raster.
The spatial reference of the Ataya tract shapefile is NAD83_StatePlane_VA_South_FIPS_4502_Feet Projected Coordinate System (Geographic Coordinate System NAD 1983).
LANDFIRE data (BpS, EVT, sClass rasters) was downloaded as “Best Fit UTM (NAD83 Datum)” so the Projected Coordinate System of the LANDFIRE rasters is NAD83_UTM_Zone_17N (Geographic Coordinate System was GCS_North American_1983). Given the size and location of our study area, we’ll use the Virginia State Plane (South) as our map coordinate system. Note: unit is feet.
Use the Project Raster tool to project each raster to the Virginia State Plane (South) coordinate system. Save the projected raster to the project geodatabase. Since the datum is the same for State Plane and UTM, no “Geographic Transformation” was needed. Resampling technique was “Nearest Neighbor” which is preferred for categorical/discrete data. Output cell size was in feet (98.425ft. = 30m.)
The three used LANDFIRE data products (BpS, EVT, sClass) provide unique aspects of land cover information. Because each raster maintains the same 30 x 30 meter cell, we can stack the LANDFIRE rasters to gain information about each arbitrary pixel within our study area.
Before we combine the rasters, take a look at the attribute table for each raster. Details on attributes can be found at landfire.gov Open the Combine tool. This tool can be found by running a search in geoprocessing or you can find it in the Spatial Analyst Toolbox. Run the combine tool using the (3) project LANDFIRE rasters: us_200bps_proj, us_200evt_proj, is_200sclass_proj. Output raster was labeled combine_landfire and saved within the project geodatabase.
Open the attribute table of the combine_landfire raster. You will notice that only the “Value” field was retained in the combine. Next we will perform joins to append tabular data to the combine_landfire raster.
Use the Join Field tool (found with a geoprocessing search) to permanently join BpS attributes to the combine_landfire raster. Follow these parameters:
This second join is to import EVT attributes. Open the Join Field Tool again and follow these parameters:
The third and final join is to import the sClass attributes. Open the Join Field tool again and follow these parameters:
To “cut” the combined raster to the boundary of our shapefile, use the Extract by Mask tool. Follow these parameters:
The resultant “combine_studyArea raster” will only contain pixels within the Ataya study region:
We choose to maintain the shape of the original raster (default setting within Extract by Mask tool), and thus the resultant extracted raster has jagged edges. Note that area calculations using the raster will differ slightly from area calculated from the vector feature.
Next, we will calculate area using raster pixel size for “combine_studyArea” raster. Follow these steps:
The sum of the Acres field corresponds to the total Ataya area (~100,653 acres).
Understanding the Field Calculation Expression
Now we’ll take our GIS attribute table and make it usable in Excel. The following steps provide instructions for turning an attribute table into a .csv file. If you want to turn the attribute table into a new excel workbook, please see the appendix.
Next, open the Ataya _combineClean.xlsx in the toDownload folder containing tutorial-specific files. This template excel spreadsheet already contains the exported Ataya attribute table in the first tab. The remaining tabs contain templates for using pivot tables to summarize the Ataya attributes.
If you performed the tutorial using your own study area rather than the Ataya study area, copy your csv into the Ataya_combineClean.xslx template spreadsheet in the place of the ataya_attribute tab. Name the spreadsheet to better represent your study area. Next, delete the OID, BpS code, Value, and DESCRIPTION columns to match what’s in our workbook.
The following sections discuss analysis of historical conditions, current conditions, land use conversion and succession classes.